We previously reported that characteristic metabolic abnormalities--which can be defined and quantitated using [18F]fluorodeoxyglucose (FDG), positron emission tomography (PET), the Scaled Subprofile Model (SSM) and factor analysis of variance (FANOVA)--distinguish patients with pareneoplastic cerebellar degeneration (PCD) from normal control subjects and correlate significantly with clinical measures of ataxia and dysarthria. Using FDG PET, we will extend our previous finding of extracerebellar metabolic covariation in PCD to hereditary and sporadic/acquired ataxia and define metabolic covariance patterns that provide quantitative indices of disease severity and progression. Our ultimate goals are to (i) define disease-related covariance patterns for the hereditary ataxias which permit classification of 'sporadic cases' in the absence of a genetic test and (ii) provide objective measures with which to monitor the efficacy of experimental therapies. Using a well- characterized motor activation protocol--sequential finger-to-thumb opposition--and [15O]water PET, we will determine the extent to which cerebellar disease affects motor activation and learning. These studies will further our understanding of the pathophysiology of cerebellar ataxia and increase the information yield of functional imaging with FDG PET. Using 2D and 3D FDG PET datasets and iterative filtered backprojection, we will investigate the impact of cerebellar atrophy on cerebellar rCMRglc and on derived patterns of metabolic covariation as a function of reconstructed image resolution. We hypothesize that increased image resolution achieved using 3D iterative filtered backprojection will decrease the confounding effect of cerebellar atrophy on PET measurements of cerebellar rCMRglc, thereby increasing our ability to detect and quantify the functional effects of cerebellar disease.